SoroushVahidi/scidocs huggingface dataset:
Bluetooth positioning using RSSI and triangulation methods
(2013)

Location based services are the hottest applications on mobile devices nowadays and the growth is continuing. Indoor wireless positioning is the key technology to enable location based services to work well indoors, where GPS normally could not work. Bluetooth has been widely used in mobile devices like phone, PAD etc. therefore Bluetooth based indoor positioning has great market potential. Radio Signal Strength (RSS) is a key parameter for wireless positioning. New Bluetooth standard (since version 2.1) enables RSS to be discovered without time consuming pre-connection. In this research, general wireless positioning technologies are firstly analysed. Then RSS based Bluetooth positioning using the new feature is studied. The mathematical model is established to analyse the relation between RSS and the distance between two Bluetooth devices. Three distance-based algorithms are used for Bluetooth positioning: Least Square Estimation, Three-border and Centroid Method. Comparison results are analysed and the ways to improve the positioning accuracy are discussed.
Parent and family impact of autism spectrum disorders: a review and proposed model for intervention evaluation.
(2012)

Raising a child with an autism spectrum disorder (ASD) can be an overwhelming experience for parents and families. The pervasive and severe deficits often present in children with ASD are associated with a plethora of difficulties in caregivers, including decreased parenting efficacy, increased parenting stress, and an increase in mental and physical health problems compared with parents of both typically developing children and children with other developmental disorders. In addition to significant financial strain and time pressures, high rates of divorce and lower overall family well-being highlight the burden that having a child with an ASD can place on families. These parent and family effects reciprocally and negatively impact the diagnosed child and can even serve to diminish the positive effects of intervention. However, most interventions for ASD are evaluated only in terms of child outcomes, ignoring parent and family factors that may have an influence on both the immediate and long-term effects of therapy. It cannot be assumed that even significant improvements in the diagnosed child will ameliorate the parent and family distress already present, especially as the time and expense of intervention can add further family disruption. Thus, a new model of intervention evaluation is proposed, which incorporates these factors and better captures the transactional nature of these relationships.
Marijuana Use in the Elderly: Implications and Considerations.
(2017)

OBJECTIVE
This article reviews the literature on the use of marijuana in the elderly. Pharmacists play an important role in the management of medications including drug use of potentially illegal drugs, including marijuana. The use of both recreational and medical marijuana has grown exponentially in the general population, including in older adults. As of 2017, marijuana for medical use is legal in 26 states and the District of Columbia.


DATA SOURCES
PubMed and Internet search using the following terms: marijuana, cannabis, delta-9-tetrhydrocannabinol (THC), cannabidiol, cannabinoid, elderly, geriatric, and pharmacology. Findings are based on data collected from older adults (65 years of age and older) through August 2016.


STUDY SELECTION
Because of the lack of research and funding, reputable literature on the impact of marijuana on older adults is scarce. The available evidence suggests that elderly individuals should be cautious when consuming marijuana, especially those who have certain comorbid conditions.


DATA EXTRACTION
The geriatric population has a higher likelihood of having multiple comorbidities and is subject to polypharmacy. Marijuana use, medicinal or recreational, complicates the picture with additive central nervous system side effects.


DATA SYNTHESIS
This article reviews the growing information on marijuana use and discusses issues to consider and cautions in usage that can apply to day-to-day clinical practice and geriatric care. The role of the pharmacist in educating patients, caregivers, and health care providers is expanding with the growing number of states that have legalized medical marijuana (26 states and the District of Columbia, as of 2017). Important education points including drug-drug interactions, drug-disease interactions, and signs and symptoms of acute overdose should be considered.


CONCLUSION
With this review, pharmacists will be informed on recommendations on the use of marijuana in the older adult. Monitoring of therapy, as well as adverse effects, will be reviewed, including some legal issues and challenges.
‘Internet Addiction’: A Critical Review
(2006)

It has been alleged by some academics that excessive Internet use can be pathological and addictive. This paper reviews what is known from the empirical literature on ‘Internet addiction’ and its derivatives (e.g., Internet Addiction Disorder, Pathological Internet Use, etc.) and assesses to what extent it exists. Empirical research into ‘Internet addiction’ can roughly be divided into five areas: (1) survey studies that compare excessive Internet users with non-excessive users, (2) survey studies that have examined vulnerable groups of excessive Internet use, most notably students, (3) studies that examine the psychometric properties of excessive Internet use, (4) case studies of excessive Internet users and treatment case studies, and (5) correlational studies examining the relationship of excessive Internet use with other behaviours (e.g., psychiatric problems, depression, self-esteem, etc.). Each of these areas is reviewed. It is concluded that if ‘Internet addiction’ does indeed exist, it affects a relatively small percentage of the online population. However, exactly what it is on the Internet that they are addicted to still remains unclear.
Title Design and realization of a smart battery management system
(2012)

Battery management system (BMS) emerges a decisive system component in battery-powered applications, such as (hybrid) electric vehicles and portable devices. However, due to the inaccurate parameter estimation of aged battery cells and multi-cell batteries, current BMSs cannot control batteries optimally, and therefore affect the usability of products. In this paper, we proposed a smart management system for multi-cell batteries, and discussed the development of our research study in three directions: i) improving the effectiveness of battery monitoring and current sensing, ii) modeling the battery aging process, and iii) designing a self-healing circuit system to compensate performance variations due to aging and other variations.
ModSpec: An open, flexible specification framework for multi-domain device modelling
(2011)

We describe ModSpec, a MATLAB/Octave based specification format suitable for modelling devices across a wide variety of application domains, including circuits, optics, fluidics and biology. The ModSpec format and associated API are centered around describing the nonlinear differential equations at the core of any device model. The format is open, general and easy to use, and is supported by toolchains that translate and automatically differentiate models, set up equations for systems of interacting devices, and provide simulation facilities. We illustrate the use of ModSpec for modelling semiconductor, photovoltaic, fluidic and neuronal devices and systems.
An efficient IP address lookup algorithm based on a small balanced tree using entry reduction
(2012)

Due to a tremendous increase in internet traffic, backbone routers must have the capability to forward massive incoming packets at several gigabits per second. IP address lookup is one of the most challenging tasks for high-speed packet forwarding. Some high-end routers have been implemented with hardware parallelism using ternary content addressable memory (TCAM). However, TCAM is much more expensive in terms of circuit complexity as well as power consumption. Therefore, efficient algorithmic solutions are essentially required to be implemented using network processors as low cost solutions. Among the state-of-the-art algorithms for IP address lookup, a binary search based on a balanced tree is effective in providing a low-cost solution. In order to construct a balanced search tree, the prefixes with the nesting relationship should be converted into completely disjointed prefixes. A leaf-pushing technique is very useful to eliminate the nesting relationship among prefixes [V. Srinivasan, G. Varghese, Fast address lookups using controlled prefix expansion, ACM Transactions on Computer Systems 17 (1) (1999) 1–40]. However, it creates duplicate prefixes, thus expanding the search tree. This paper proposes an efficient IP address lookup algorithm based on a small balanced tree using entry reduction. The leaf-pushing technique is used for creating the completely disjointed entries. In the leaf-pushed prefixes, there are numerous pairs of adjacent prefixes with similarities in prefix strings and output ports. The number of entries can be significantly reduced by the use of a new entry reduction method which merges pairs with these similar prefixes. After sorting the reduced disjointed entries, a small balanced tree is constructed with a very small node size. Based on this small balanced tree, a native binary search can be effectively used in address lookup issue. In addition, we propose a new multi-way search algorithm to improve a binary search for IPv4 address lookup. As a result, the proposed algorithms offer excellent lookup performance along with reduced memory requirements. Besides, these provide good scalability for large amounts of routing data and for the address migration toward IPv6. Using both various IPv4 and IPv6 routing data, the performance evaluation results demonstrate that the proposed algorithms have better performance in terms of lookup speed, memory requirement and scalability for the growth of entries and IPv6, as compared with other algorithms based on a binary search. 2011 Elsevier B.V. All rights reserved. . All rights reserved. x: +82 2 313 8053.
Happiness Runs in a Circular Motion : Evidence for a Positive Feedback Loop between Prosocial Spending and Happiness
(2012)

We examine whether a positive feedback loop exists between spending money on others (i.e. prosocial spending) and happiness. Participants recalled a previous purchase made for either themselves or someone else and then reported their happiness. Afterward, participants chose whether to spend a monetary windfall on themselves or someone else. Participants assigned to recall a purchase made for someone else reported feeling significantly happier immediately after this recollection; most importantly, the happier participants felt, the more likely they were to choose to spend a windfall on someone else in the near future. Thus, by providing initial evidence for a positive feedback loop between prosocial spending and well-being, these data offer one potential path to sustainable happiness: prosocial spending increases happiness which in turn encourages prosocial spending.
Accessory Axillary Breast Tissues
(2006)

Dr. Emsen recently published a case report describing a patient with accessory axillary breast tissue treated with ultrasound-guided liposuction [3]. We recently treated a similar case of bilateral axillary breast tissue, and we offer our contribution to the debate (Figs. 1, 2). Accessory axillary breast tissues are common embriogenic alterations found in 1% to 6% of women that often manifest bilaterally [1,2]. Ectopic breast tissue is at risk for benign and malignant breast disease with reported diagnoses of fibrocystic disease, mastitis, fibroadenoma, atypical hyperplasia, and carcinoma [4 6]. In a review of 82 ectopic breast cancer cases, Marshall et al. [5] found an increased incidence of cancer in aberrant breast tissue. Ectopic cancers located in the axilla seemed to present with more extensive disease at an earlier age, suggesting that aberrant breast tissue may be at increased risk for malignant change. According to this view, as for any ectopic mass, tissue diagnosis is required and mandatory [4]. We recently treated a 43-year-old woman who was asymptomatic until her second pregnancy (2004), when two bilateral masses appeared in axillae and began to increase in size. Six months after parturition, a clear fluid was continuously secreted throughout few small pores on the skin. Ultrasounddiagnosed breast tissue and excision with histologic examination confirmed the radiologic findings. In this case, we preoperatively contemplated, as Dr. Emsen did, less invasive and aesthetic methods such as liposuction. However, a collegial discussion with our pathologist and an analysis of literature data suggested en bloc removal for a more precise analysis not only of cellular, but also of histologic characteristics of suspected mammary ducts. We believe that liposuction, more traumatic on tissues than simple excision, does not allow for this. Furthermore, although liposuction leaves minimal incision scars, the Fig. 1. A 43-year-old woman. Right axilla with accessory breast tissue.
2D ear classification based on unsupervised clustering
(2014)

Ear classification refers to the process by which an input ear image is assigned to one of several pre-defined classes based on a set of features extracted from the image. In the context of large-scale ear identification, where the input probe image has to be compared against a large set of gallery images in order to locate a matching identity, classification can be used to restrict the matching process to only those images in the gallery that belong to the same class as the probe. In this work, we utilize an unsupervised clustering scheme to partition ear images into multiple classes (i.e., clusters), with each class being denoted by a prototype or a centroid. A given ear image is assigned class labels (i.e., cluster indices) that correspond to the clusters whose centroids are closest to it. We compare the classification performance of three different texture descriptors, viz. Histograms of Oriented Gradients, uniform Local Binary Patterns and Local Phase Quantization. Extensive experiments using three different ear datasets suggest that the Local Phase Quantization texture descriptor scheme along with PCA for dimensionality reduction results in a 96.89% hit rate (i.e., 3.11% pre-selection error rate) with a penetration rate of 32.08%. Further, we demonstrate that the hit rate improves to 99.01% with a penetration rate of 47.10% when a multi-cluster search strategy is employed.
Beyond the PDP-11: Architectural Support for a Memory-Safe C Abstract Machine
(2015)

We propose a new memory-safe interpretation of the C abstract machine that provides stronger protection to benefit security and debugging. Despite ambiguities in the specification intended to provide implementation flexibility, contemporary implementations of C have converged on a memory model similar to the PDP-11, the original target for C. This model lacks support for memory safety despite well-documented impacts on security and reliability.
 Attempts to change this model are often hampered by assumptions embedded in a large body of existing C code, dating back to the memory model exposed by the original C compiler for the PDP-11. Our experience with attempting to implement a memory-safe variant of C on the CHERI experimental microprocessor led us to identify a number of problematic idioms. We describe these as well as their interaction with existing memory safety schemes and the assumptions that they make beyond the requirements of the C specification. Finally, we refine the CHERI ISA and abstract model for C, by combining elements of the CHERI capability model and fat pointers, and present a softcore CPU that implements a C abstract machine that can run legacy C code with strong memory protection guarantees.
Design principles for sensemaking support systems in environmental sustainability transformations
(2018)

Correspondence: Stefan Seidel, University of Liechtenstein, Fuerst-Franz-Josef-Strasse 23, 9490 Vaduz, Liechtenstein. Tel: +423 265 1303; E-mail: stefan.seidel@uni.li Abstract This paper reports on the results of a design science research (DSR) study that develops design principles for information systems (IS) that support organisational sensemaking in environmental sustainability transformations. We identify initial design principles based on salient affordances required in organisational sensemaking and revise them through three rounds of developing, demonstrating and evaluating a prototypical implementation. Through our analysis, we learn how IS can support essential sensemaking practices in environmental sustainability transformations, including experiencing disruptive ambiguity through the provision of environmental data, noticing and bracketing, engaging in an open and inclusive communication and presuming potential alternative environmentally responsible actions. We make two key contributions: First, we provide a set of theory-inspired design principles for IS that support sensemaking in sustainability transformations, and revise them empirically using a DSR method. Second, we show how the concept of affordances can be used in DSR to investigate how IS can support organisational practices. While our findings are based on the investigation of the substantive context of environmental sustainability transformation, we suggest that they might be applicable in a broader set of contexts of organisational sensemaking and thus for a broader class of sensemaking support systems. European Journal of Information Systems (2017). doi:10.1057/s41303-017-0039-0
Transforming Web Tables to a Relational Database
(2014)

HTML tables represent a significant fraction of web data. The often complex headers of such tables are determined accurately using their indexing property. Isolated headers are factored to extract category hierarchies. Web tables are then transformed into a canonical form and imported into a relational database. The proposed processing allows for the formulation of arbitrary SQL queries over the collection of induced relational tables. Keywords—table segmentation; Wang categories; header paths; relational table SQL queries
MULTIPLE-ATTRIBUTE TEXT REWRITING
(2018)

The dominant approach to unsupervised “style transfer” in text is based on the idea of learning a latent representation, which is independent of the attributes specifying its “style”. In this paper, we show that this condition is not necessary and is not always met in practice, even with domain adversarial training that explicitly aims at learning such disentangled representations. We thus propose a new model that controls several factors of variation in textual data where this condition on disentanglement is replaced with a simpler mechanism based on back-translation. Our method allows control over multiple attributes, like gender, sentiment, product type, etc., and a more fine-grained control on the trade-off between content preservation and change of style with a pooling operator in the latent space. Our experiments demonstrate that the fully entangled model produces better generations, even when tested on new and more challenging benchmarks comprising reviews with multiple sentences and multiple attributes.
Activity Recognition and Abnormal Behaviour Detection with Recurrent Neural Networks
(2017)

In this paper, we study the problem of activity recognition and abnormal behaviour detection for elderly people with dementia. Very few studies have attempted to address this problem presumably because of the lack of experimental data in the context of dementia care. In particular, the paper investigates three variants of Recurrent Neural Networks (RNNs): Vanilla RNNs (VRNN), Long Short Term RNNs (LSTM) and Gated Recurrent Unit RNNs (GRU). Here activity recognition is considered as a sequence labelling problem, while abnormal behaviour is flagged based on the deviation from normal patterns. To provide an adequate discussion of the performance of RNNs in this context, we compare them against the state-of-art methods such as Support Vector Machines (SVMs), Naı̈ve Bayes (NB), Hidden Markov Models (HMMs), Hidden Semi-Markov Models (HSMM) and Conditional Random Fields (CRFs). The results obtained indicate that RNNs are competitive with those state-of-art methods. Moreover, the paper presents a methodology for generating synthetic data reflecting on some behaviours of people with dementia given the difficulty of obtaining real-world data. c 6 t r . ublis e ls i r . . i ilit f t f re ce r ra hairs.
Community Evaluation and Exchange of Word Vectors at wordvectors.org
(2014)

Vector space word representations are useful for many natural language processing applications. The diversity of techniques for computing vector representations and the large number of evaluation benchmarks makes reliable comparison a tedious task both for researchers developing new vector space models and for those wishing to use them. We present a website and suite of offline tools that that facilitate evaluation of word vectors on standard lexical semantics benchmarks and permit exchange and archival by users who wish to find good vectors for their applications. The system is accessible at: www.wordvectors.org.
Central pattern generators for locomotion control in animals and robots: A review
(2008)

The problem of controlling locomotion is an area in which neuroscience and robotics can fruitfully interact. In this article, I will review research carried out on locomotor central pattern generators (CPGs), i.e. neural circuits capable of producing coordinated patterns of high-dimensional rhythmic output signals while receiving only simple, low-dimensional, input signals. The review will first cover neurobiological observations concerning locomotor CPGs and their numerical modelling, with a special focus on vertebrates. It will then cover how CPG models implemented as neural networks or systems of coupled oscillators can be used in robotics for controlling the locomotion of articulated robots. The review also presents how robots can be used as scientific tools to obtain a better understanding of the functioning of biological CPGs. Finally, various methods for designing CPGs to control specific modes of locomotion will be briefly reviewed. In this process, I will discuss different types of CPG models, the pros and cons of using CPGs with robots, and the pros and cons of using robots as scientific tools. Open research topics both in biology and in robotics will also be discussed.
Inverse Kinematics for a Point-Foot Quadruped Robot with Dynamic Redundancy Resolution
(2007)

In this work we examine the control of center of mass and swing leg trajectories in LittleDog, a point-foot quadruped robot. It is not clear how to formulate a function to compute forward kinematics of the center of mass of the robot as a function of actuated joint angles because point-foot walkers have no direct actuation between the feet and the ground. Nevertheless, we show that a whole-body Jacobian exists and is well defined when at least three of the feet are on the ground. Also, the typical approach of work-space centering for redundancy resolution causes destabilizing motions when executing fast motions. An alternative redundancy resolution optimization is proposed which projects single-leg inverse kinematic solutions into the nullspace. This hybrid approach seems to minimize 1) unnecessary rotation of the body, 2) twisting of the stance legs, and 3) whole-body involvement in achieving a step leg trajectory. In simulation, this control allows the robot to perform significantly more dynamic behaviors while maintaining stability.